The capability of reliably balancing color gamut between cameras with different characteristics is a significant need for many application domains. When dealing with panoramic image formation, i.e., image stitching, the availability of color balanced input images is particularly crucial, since the human vision system is incredibly skilled in spotting color differences in adjacent images.
Exemplary color balancing methods fall in 2 categories:                Hardware camera register calibration,        Camera image post-processing.        
The methods in the first category modify the internal camera registers, e.g., gain, exposure, etc., in order to obtain some desired color response. The general idea of the hardware calibration is to use a general optimizer to search the space of each camera's hardware register values for a state with the closest match between the colors of a target image and the camera image of the color chart. For each camera, the optimizer repeatedly adjusts the register values, acquires an image, and computes the cost. The optimizer typically runs until all the cameras are close enough to the target image, or until there is no significant improvement from the previous iteration. Hardware camera register calibration, however, is typically insufficient to achieve color consistency, because their range and precision are often inadequate.
Therefore, methods of the second category, where images after the acquisition are processed and color a calibration is performed, are desirable. Those methods provide a more precise refinement.
Additionally, a combination of the two mentioned classes could be considered, where both camera internal register calibration and image post-processing refinement are applied.
The above-mentioned exemplary color balancing approaches though suffer from a number of problems:                They perform the color calibration only with respect to a known target containing standardized color samples        In case the system has to be re-calibrated, e.g., illumination conditions of the working environment changed, the necessity of using a pre-defined pattern represents a lack of flexibility        The cameras to be calibrated need to have an overlapping field of view. The overlapping area between the cameras that have to be color balanced has to be large enough to contain the color calibration pattern. Or if there is no calibration pattern, then only a color matching is performed between two cameras, but not balancing of the color gamut.        In large camera arrays, where the shared field of view is minimized, this requirement is a strict constraint.        